DISCOVERING THE CHEMICAL FACTORS BEHIND REGIONAL ROYAL JELLY DIFFERENCES VIA MACHINE LEARNING Makine Öğrenimi Yoluyla Bölgesel Arı Sütü Farklarının Arkasındaki Kimyasal Faktörleri Keşfetmek

ÖZKÖK A., KESKİN M., Tanuğur Samanci A. E., Yorulmaz Önder E., SİLAHTAROĞLU G.

Uludag Aricilik Dergisi, cilt.23, sa.1, ss.49-60, 2023 (Scopus) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 23 Sayı: 1
  • Basım Tarihi: 2023
  • Doi Numarası: 10.31467/uluaricilik.1238027
  • Dergi Adı: Uludag Aricilik Dergisi
  • Derginin Tarandığı İndeksler: Scopus, Academic Search Premier, TR DİZİN (ULAKBİM)
  • Sayfa Sayıları: ss.49-60
  • Anahtar Kelimeler: 10-HDA, honeybee, machine learning, Royal jelly
  • Hacettepe Üniversitesi Adresli: Evet

Özet

This study aims to discover the characteristic chemical factors for determining the region of royal jelly using machine learning. 84 samples from 13 different regions of Turkey were used for the study, and the chemical parameters of moisture, pH, acidity, and 10-hydroxy-2-decanoic acid (10-HDA) were investigated. ANOVA test was conducted to determine whether there are differences between royal jelly from 13 locations concerning the four chemical values. In addition to the statistical tests, a machine learning model was used to find out what makes royal jelly different from each other. The descriptive statistics of the chemical analysis results of royal jelly showed the following values: moisture 63.05%±2.99, pH 3.67±0.08, acidity 45.32±3.55, and 10-HDA 2.40±0.24. Surprisingly, the machine learning model suggests that 10-HDA may be the most prominent parameter for determining the region of royal jelly. This information will help us identify royal jelly’s authenticity more easily.